1. Introduction
The COVID-19 outbreak has raised enrollments in massive open online courses (MOOCs) in recent years [
1]. MOOCs are a collection of ego web-based learning materials [
2,
3]. According to Cope and Kalantzis [
4], MOOCs are one of the numerous instruments afforded by ICTs applied to education. MOOCs are a relatively new learning phenomenon, blending eLearning and open education [
5]. Their name comes from the concept of multi-player online game (MMOG) [
4]. They are not the same as open or distant learning. In 1995, Mr. Jerrold Maddox of Penn State University in the United States offered the first online “Commentary on Art” course. Only four years later, the term “eLearning” was developed. The UK government made loans accessible to students enrolled in bachelor distance learning programs for the first time in 2013. It is important to distinguish between eLearning and MOOCs. Electronic technology and digital media are being used to supplement or even totally supplant in-class educational experiences with fully online learning [
6,
7]. MOOCs, on the other hand, can only benefit a student’s learning experience if they are not administered according to strict guidelines. Significant elements, such as finance, advertising, legal problems, scaffolding, learner connection, and alignment with learning aims, must all be considered when implementing MOOCs [
8,
9]. MOOCs must guarantee that those that have registered keep learning from the courses that are available to them as the number of persons participating in MOOCs expands [
10].
Previous studies have identified many reasons for individuals quitting MOOCs as a learning medium [
3,
9,
11,
12,
13]. MOOC completion rates are low, demonstrating a lack of self-control and motivation compared to what is expected of students [
3,
11,
14]. As students go through the course material, their efficiency drops [
14]. Furthermore, these MOOCs do not ensure the effectiveness of educational elements, nor do they give any support and funding for entrant motivation or social connection formation [
13,
15,
16]. Finally, MOOCs are founded on students’ dedication to their learning goals, prior knowledge and abilities, and shared support [
17,
18]. Though the benefits and drawbacks of MOOCs have been debated [
19,
20], the effect of MOOCs on institutions of higher learning cannot be ignored. As a result, researching the viability and advantages of massive open online courses (MOOCs) as part of an academic program is crucial. MOOCs are a divisive topic, both in terms of their utilization and the possible consequences for advanced learning. MOOCs, according to a group of professors, do not suit the needs of students [
18]. One instance is the poor student turnover rate in these programs. Another theory is that MOOCs might cause severe worries about higher education, especially in terms of research and development [
19,
20]. Because of their economic model, MOOCs have the potential to destabilize higher-education institutions by disrupting the relationship between the three parts that make up university operations: teaching, research, and program consumer lending. MOOCs, according to some experts [
21], offer a huge potential for helping people since they enable flexible, inexpensive access and speedy completion for anybody who wants to learn [
22]. One of the most crucial problems discussed during COVID-19 [
19] was academic recognition, a community conversation concerning the influence of MOOCs on higher education. Additionally, even if there is a possibility that MOOCs will have a detrimental influence on higher education, it appears that there is a willingness to analyze the advantages and reach judgments during the height of the MOOC discussion. The benefits include promotion of the university’s national objectives, which are connected to online classes and internet core skills at Saudi Arabian universities, as well as advancement of the institution’s global status, international student appeal, and promotion of the university’s nationwide aims. The role of King Faisal University in integrating MOOCs into the academic curriculum is examined in this paper, which aims to make suggestions for further MOOC incorporation in Saudi Arabian higher education.
As a consequence, by examining the links between TAM variables’ originality, knowledge management (KM) characteristics, and innovation diffusion theory (IDT) in a comparable model, this work contributes to the TAM literature. Using KM as a contextual theory, the study aims to assess the impact of inspirational variables on IDT and TAM ideas. As a result, eight factors were discovered to be determining factors of perceived usefulness and ease of use, different values, attitude toward using MOOC systems, and intention to use MOOCs: subjective norm, applying new fit, perceived suitability, trialability, quantitative measurements, awareness, knowledge application, and knowledge sharing. The empirical study could help academics and practitioners create and sell MOOC systems by assisting them in designing and testing concepts to scheme recognition.
The Impact of MOOC Use in Saudi Higher Education
The Kingdom of Saudi Arabia is determined to stay up to date with the advancement of global higher-education institutions. As a result, the Ministry of Higher Education held the first international conference on massive open online courses (MOOCs) and remote learning [
23]. The spread of COVID-19 prompted the closure of educational facilities across the world in 2020, as a result of the COVID-19 pandemic. As a result of the shutdown, those schools’ online learning environments improved, and learning and teaching were no longer disturbed [
24]. During the COVID-19 pandemic, the Saudi university’s preparation for a complete MOOC system shift experience is put to the test, addressing obstacles students have when attending MOOC courses by comparing Saudi student challenges to the findings of several studies. According to the research, judging students’ work is challenging, and speaking into a vacuum owing to the lack of rapid student reaction, being burdened by large time and financial obligations, and confronting a lack of student engagement in online forums are all issues [
25,
26]. The biggest difficulty that MOOC providers confront is poor adoption rates, particularly in developing countries [
27]. Meanwhile, Saudi Arabian colleges have embraced MOOCs; for example, King Khalid University (2012) provides MOOCs so that all of its lectures are accessible online. MOOCs have the ability to update the Saudi workforce and improve the education system by providing high-skilled training programs [
28], but only if students accept the MOOC approach. As a result, it is important to establish what elements influence learners’ adoption of MOOCs. A MOOC is a free, open access online course, in which students follow a well-defined syllabus with stated learning goals while watching recorded videos or participating in asynchronous learning activities. Ego and freedom in deciding to engage in MOOCs due to self, as well as self-assessed preparedness of past knowledge and abilities [
4], are the key concepts behind MOOCs. Because of the growing popularity of these MOOCs, some institutions and universities have decided to include them in their curricula [
8].
5. Discussion and Implications
MOOCs provide students with ubiquitous access to a variety of materials in “anytime, anywhere” situations. MOOCs give sufficient storage capacity for students to save their content. Students can also exchange material content with their classmates through MOOCs. Management, engineering, and science and technology students may use what they have learned in MOOCs for decision-making and problem-solving tasks. Nonetheless, there are a number of elements that may influence students’ decision to use MOOCs. Due to the cultural backgrounds of the pupils, these elements differ from one nation to the next. The goal of this study was to develop and test a model by looking into KM, IDT, and TAM theories, such as expertise access, application of knowledge, knowledge sharing, user satisfaction, perceived advantages, viewed compatibility, tangibility, observability as dimensions of PEOU, PU, and attitude toward using MOOC system on students’ intention to use MOOCs across different cultures, specifically Saudi Arabia.
The hypothesized correlations were evaluated using SEM analysis using SPSS-AMOS 23. Knowledge sharing (β = 0.585, t-value = 12.934;
p < 0.001; β = 0.068, t-value = 2.194,
p < 0.001), knowledge application (β = −0.167, t-value = −2.224
p < 0.001; β = 0.418, t-value = 9.183
p < 0.001), and knowledge access (β = 0.117, t-value = 2.152,
p < 0.001) were shown to be the most common As a result. H1, H2, H3, H4, H5, and H6 were shown to be viable options. The findings revealed a positive and substantial association, supporting hypotheses (H1–H6) that students value MOOCs for knowledge sharing, knowledge application, and information access, and anticipate utilizing them to improve their educational performance. These results support previous research [
81,
82], which revealed that ease of use utility boosted students’ active learning, application, and sharing.
According to TAM, students’ perceptions toward MOOCs and their motivation to participate in MOOC programs were influenced by perceived enjoyment, perceived technical fit, perceived utility, and considered ease of use. This was the case in this study, where users of MOOC systems thought that a higher perceived usefulness equaled a greater willingness to use the MOOC systems. Perceived technology fit does not have a positive and significant impact on the perceived usefulness (β = −0.004, t-value = −0.109,
p < 0.001). Therefore, hypothesis (H7) indicates that there is not a relationship between perceived technology fit on perceived usefulness; thus, H7 was unsupported. However, perceived technology fit was positively associated with the perceived ease of use (β = −0.056, t-value = −2.190,
p < 0.05) and, therefore, H8 was accepted. Moreover, perceived enjoyment has a significant beneficial effect on perceived usefulness (β = −0.165, t-value = −4.208,
p < 0.001) and PEOU (β = 0.111, t-value = 4.206,
p < 0.001). Thereby, H9 and H10 were supported. These outcomes were similar to those in [
54].
The results of the path coefficients are shown in
Figure 4 and
Table 3. For hypotheses (H11–H16), observability has an influence on perceived usefulness (β = 0.186, t-value = 2.387,
p < 0.001) and perceived ease of use (β = −0.235, t-value = −4.501,
p < 0.001), trialability on perceived usefulness (β = 0.408, t-value = 5.141,
p < 0.001) and perceived ease of use (β = 0.585, t-value = 13.753,
p < 0.001), and perceived compatibility on perceived usefulness (β = 0.145, t-value = 3.608,
p < 0.001) for MOOCs. These findings are in line with a prior study [
87,
88], which found that perceived ease of use and perceived utility increased students’ observability, trialability, and perceived compatibility. Perceived compatibility, on the other hand, was negatively linked with the PEOU (β = −0.028, t-value = −1.013,
p < 0.001); hence, H12 was rejected. Perceived compatibility, on the other hand, had no positive or substantial influence on PEOU; consequently, H12 was not supported.
This research also showed that perceived ease of use had a positive effect on perceived usefulness. Therefore, hypothesis (H17) demonstrated that there was a positive relationship between perceived ease of use and perceived usefulness (β = 0.257, t-value = 4.437,
p < 0.001); thus, H17 was supported. Similarly, the relationship between PEOU on PU (H18) was (β = −0.310, t = −3.606,
p < 0.001). Thereby, the hypothesis was accepted. Moreover, H19 was supported. PEOU has a significant positive effect on the attitude towards using MOOC systems (β = 0.514, t = 9.308,
p < 0.001). Nonetheless, the test findings were the same as in previous reports [
87,
88].
Finally, attitude towards using MOOC systems was positively associated with the MOOCs (β = 0.399, t = 7.666,
p < 0.001) and, therefore, H20 was accepted. On the other hand, the attitude toward utilizing the MOOC system has a favorable and significant influence on the intention to utilize MOOCs; hence, H20 was endorsed. These findings back a prior study [
89,
90], which found that students’ views on utilizing MOOC platforms were all impacted by their parents. This research presents three pieces of evidence. Perceived usefulness and ease of use were the first empirical evidence of the MOOC system, and the second was evidence of attitude toward using the MOOC system, as measured through perceived usefulness and ease of use, which may influence the intention to use MOOCs. Knowledge sharing, knowledge access, and knowledge application provided the last empirical proof that perceived usefulness and ease of use of MOOC systems may impact students’ perceptions about utilizing MOOC systems. In the educational environment, there was a substantial theoretical addition to prior knowledge management components (KM), IDT with TAM [
76,
91,
92]. Education must open the door to questioning the entire concept of sustainable development as the proper way and motivate today’s and tomorrow’s students to build new ideas and paradigms in order to make the world a better place [
93,
94].
Limitations and Future Work
In addition to contributions in determining the antecedents of knowledge management (KM), IDT, and TAM and their influence on MOOC use intention, there are some limitations in this study. First, the sample size of the research was limited to one university in Saudi Arabia. Therefore, the results may not reveal the performance of private universities, militaries, or school teachers. Second, this study excluded the UTAUT factors (performance expectancy, social influence, and facilitating conditions), and the participants in this study were selected randomly from one university. Future studies must take into account a number of important restrictions. To begin, only questionnaire surveys were employed to gather information. As a result, future attempts may look into employing qualitative methods, such as interviews or focus groups, to better understand and confirm the quantitative findings. Second, the model should be expanded to include other components such as contentment with the system and confirmation. Third, the three moderators (age, gender, and experiences) were not included in this study, and the participants were chosen at random from one institution; future studies should use diverse samples from different universities to investigate the impact of these moderators on the model. Finally, while the sample size was enough for examining the model and performing the structural equation model analysis, bigger sample sizes should be used in future investigations.